class_docstr: Sigmoid cross entropy gradient function.
class_docstr_tok: ["Sigmoid","cross","entropy","gradient","function","."]
code: def backward(self, indexes, grad_outputs):
      (ggx,) = grad_outputs
      x, gy = self.get_retained_inputs()
      y = chainer.functions.sigmoid(x)
      yp = y * (1 - y)
      gx = yp * chainer.functions.broadcast_to(gy, yp.shape)
      ggy = y - self.t.astype(y.dtype)
      gx *= self.ignore_mask * ggx
      ggy *= self.ignore_mask * ggx
  
      if self.reduce == "mean":
          gx /= self.count
          ggy = chainer.functions.sum(ggy) / self.count
  
      return gx, ggy
  
file_path: chainer/chainer/functions/loss/sigmoid_cross_entropy.py
imports: import chainer
  from chainer import backend
  from chainer import function_node
  from chainer.functions.activation import sigmoid
  from chainer import utils
  from chainer.utils import type_check
label_desc: Use image node_id 3 for calling the SigmoidCrossEntropyGrad obj's underlying member method code with example usage: obj.backward(indexes, grad_outputs) and returns: gx,  ggy